Update app.py

app.py

@@ -36,15 +36,15 @@ pipe = pipeline("automatic-speech-recognition", model="openai/whisper-large")
 def slider_logic(slider):
     threshold = 0
     if slider == 1:
-        threshold = .88
+        threshold = .98
     elif slider == 2:
-        threshold = .78
+        threshold = .88
     elif slider == 3:
-        threshold = .67
+        threshold = .78
     elif slider == 4:
-        threshold = .56
+        threshold = .68
     elif slider == 5:
-        threshold = .45
+        threshold = .58
     else:
         threshold = []
     return threshold
@@ -95,6 +95,7 @@ def classify_toxicity(audio_file, selected_sounds, slider):
         if selected_class_name in class_score_dict:
             score = class_score_dict[selected_class_name]
             matching_label_score[selected_class_name] = score
+            print("matching label score type is ", type(matching_label_score))
     
     #  iterate through matching_label_score to check if any scores exceed the threshold
     for label, score in matching_label_score.items():